Bioinformatics Education—Perspectives and Challenges

This article discusses the evolution of curriculum, instructional methodologies and initiatives supporting the dissemination of bioinformatics. Building on the early applications of informatics to the field of biology, bioinformatics research entails input from the diverse disciplines of mathematics and statistics, physics and chemistry and medicine and pharmacology. Training in bioinformatics remains the oldest and most important rapid introduction approach to learning bioinformatics skills.2 page(s

An analysis of the Covid-19 Market Crash in Korea

학위논문(석사) -- 서울대학교대학원 : 경영대학 경영학과, 2021.8. 최동범.본 연구는 Covid-19에 따른 한국 주식시장의 급락 이벤트를 활용하여 기업의 환경∙사회책임 활동이 주주가치를 개선한다고 보는 시각과 기업의 환경∙사회책임 활동은 대리인 문제에 따른 결과로 보는 시각을 각각 테스트하였다. 먼저, 주주가치 개선의 시각에서는 주식 급락시장에서 ESG평가등급이 높은 주식이 양의 누적수익률을 가질 것으로 예측한다. 2020년 1분기 이벤트 기간의 누적수익률을 한국기업지배구조원의 E등급과 S등급을 평균한 점수에 따라 비교한 결과, 평균점수가 높을수록 유의한 음의 누적수익률을 가지는 것으로 나타났다. 또한, 이중차분모형 분석 결과 이러한 음의 효과는 이벤트 기간에서만 유효한 것으로 나타났다. 대리인비용 견해에 부합하는지 검증하기 위해 한국기업지배구조원의 E와 S 등급을 평균하여 얻은 ES변수는 투자비용과 양의 관계를 가진다는 첫번째 가설과 한국의 환경∙사회책임 우수기업은 이벤트 기간 이전에 환경∙사회적 투자가 많았을 것이라는 두번째 가설을 세웠다. ES 변수에 대한 회귀 분석 결과, ES 변수는 판매및관리비와 유의한 양의 관계를 가지며 회사규모 및 배당수익률의 함수임을 확인하였다. 다음으로, 투자비용에 대한 이중차분모형 분석 결과, 이벤트 이전의 기간 동안 ES 변수와 환경∙사회책임 우수기업의 투자비용간 유의한 양의 관계를 가지지만 이벤트 기간에는 ES변수와 투자비용간 유의한 관계가 사라짐을 확인하였다. 본 연구는 비교적 연구가 활발히 진행되지 않던 경제침체 기간 동안 ESG 평가등급과 주식수익률 간의 관계에 대한 실증 분석결과를 제시하였다. 또한, ESG 분야에서 지배적인 입장을 가지는 주주가치 개선 가설(value-enhancing ESG perspective)에 반대되고 대리인비용 가설 (agency perspective on ESG)에 부합하는 실증결과를 제공하였다는데 연구의 의미가 있다.In this paper, I revisit the question of whether ESG activities are value-maximizing or agent-driven in the Korean stock market using the Covid-19 panic period. I document a unique and negative association between ESG scores and stock returns during the first quarter of 2020. I find that ESG score is a function of selling, general and administrative (SG&A) costs and that high-ESG firms increased their overall costs, SG&A, and free cash flows relative to low-ESG firms before the onset of Covid-19 pandemic. I argue that overinvestment before the first quarter of 2020 significantly accounts for the worse stock performance of socially responsible firms.1. Introduction 2 2. Data 6 2.1. ES measure 6 2.2. Event period 7 2.3. Return and control variables 8 2.4. Summary statistics 10 3. Covid-19 Panic period experiment 11 3.1. Empirical design 11 3.2. Empricial results 13 3.2.1. Panic period cross-sectional regression 13 3.2.2. Difference-in-differences regression 16 4. Overinvestment 18 4.1. Determinants of ES 19 4.2. Firms’ Expenditure surrounding the panic period 23 5. Conclusion 27 Reference 28 Abstract in Korean 44석

Privacy-preserving outsourced support vector machine design for secure drug discovery

AXA Research Fund, Singapore Management Universit

Label Shift Adapter for Test-Time Adaptation under Covariate and Label Shifts

Test-time adaptation (TTA) aims to adapt a pre-trained model to the target domain in a batch-by-batch manner during inference. While label distributions often exhibit imbalances in real-world scenarios, most previous TTA approaches typically assume that both source and target domain datasets have balanced label distribution. Due to the fact that certain classes appear more frequently in certain domains (e.g., buildings in cities, trees in forests), it is natural that the label distribution shifts as the domain changes. However, we discover that the majority of existing TTA methods fail to address the coexistence of covariate and label shifts. To tackle this challenge, we propose a novel label shift adapter that can be incorporated into existing TTA approaches to deal with label shifts during the TTA process effectively. Specifically, we estimate the label distribution of the target domain to feed it into the label shift adapter. Subsequently, the label shift adapter produces optimal parameters for the target label distribution. By predicting only the parameters for a part of the pre-trained source model, our approach is computationally efficient and can be easily applied, regardless of the model architectures. Through extensive experiments, we demonstrate that integrating our strategy with TTA approaches leads to substantial performance improvements under the joint presence of label and covariate shifts.Comment: Accepted to ICCV 202

HistRED: A Historical Document-Level Relation Extraction Dataset

Despite the extensive applications of relation extraction (RE) tasks in various domains, little has been explored in the historical context, which contains promising data across hundreds and thousands of years. To promote the historical RE research, we present HistRED constructed from Yeonhaengnok. Yeonhaengnok is a collection of records originally written in Hanja, the classical Chinese writing, which has later been translated into Korean. HistRED provides bilingual annotations such that RE can be performed on Korean and Hanja texts. In addition, HistRED supports various self-contained subtexts with different lengths, from a sentence level to a document level, supporting diverse context settings for researchers to evaluate the robustness of their RE models. To demonstrate the usefulness of our dataset, we propose a bilingual RE model that leverages both Korean and Hanja contexts to predict relations between entities. Our model outperforms monolingual baselines on HistRED, showing that employing multiple language contexts supplements the RE predictions. The dataset is publicly available at: https://huggingface.co/datasets/Soyoung/HistRED under CC BY-NC-ND 4.0 license

Development of ListeriaBase and comparative analysis of Listeria monocytogenes

Background: Listeria consists of both pathogenic and non-pathogenic species. Reports of similarities between the genomic content between some pathogenic and non-pathogenic species necessitates the investigation of these species at the genomic level to understand the evolution of virulence-associated genes. With Listeria genome data growing exponentially, comparative genomic analysis may give better insights into evolution, genetics and phylogeny of Listeria spp., leading to better management of the diseases caused by them. Description: With this motivation, we have developed ListeriaBase, a web Listeria genomic resource and analysis platform to facilitate comparative analysis of Listeria spp. ListeriaBase currently houses 850,402 protein-coding genes, 18,113 RNAs and 15,576 tRNAs from 285 genome sequences of different Listeria strains. An AJAX-based real time search system implemented in ListeriaBase facilitates searching of this huge genomic data. Our in-house designed comparative analysis tools such as Pairwise Genome Comparison (PGC) tool allowing comparison between two genomes, Pathogenomics Profiling Tool (PathoProT) for comparing the virulence genes, and ListeriaTree for phylogenic classification, were customized and incorporated in ListeriaBase facilitating comparative genomic analysis of Listeria spp. Interestingly, we identified a unique genomic feature in the L. monocytogenes genomes in our analysis. The Auto protein sequences of the serotype 4 and the non-serotype 4 strains of L. monocytogenes possessed unique sequence signatures that can differentiate the two groups. We propose that the aut gene may be a potential gene marker for differentiating the serotype 4 strains from other serotypes of L. monocytogenes. Conclusions: ListeriaBase is a useful resource and analysis platform that can facilitate comparative analysis of Listeria for the scientific communities. We have successfully demonstrated some key utilities of ListeriaBase. The knowledge that we obtained in the analyses of L. monocytogenes may be important for functional works of this human pathogen in future. ListeriaBase is currently available at http://listeria.um.edu.my

Privacy-preserving outsourced calculation toolkit in the cloud

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Investigating America online instant messaging application: data remnants on windows 8.1 client machine

Instant messaging applications (apps) are one potential source of evidence in a criminal investigation or a civil litigation. To ensure the most effective collection of evidence, it is vital for forensic practitioners to possess up-to-date knowledge about artifacts of forensic interest from various instant messaging apps. Hence, in this chapter we study America Online Instant Messenger (version 7.14.5.8) with the aims of contributing to an in-depth understanding of the types of terrestrial artifacts that are likely to remain after the use of instant messaging services and apps on Windows 8.1 devices. Potential artifacts identified during the research include data relating to the installation or uninstallation, log-in and log-off information, contact lists, conversations, and transferred files

An Early Presenting Esophageal Schwannoma

Esophageal schwannoma is a rare diagnosis and historically has been a tumor of middle-aged females. We report a case of a 22-year-old male presenting initially with dyspnea secondary to tracheal compression from an 8 × 6 × 3.0 cm esophageal schwannoma. The tumor was surgically resected, and diagnosis was confirmed with immunohistochemical and pathological studies. We report the youngest case of esophageal schwannoma in an otherwise healthy individual